A research report submitted to the School of Social Sciences, Faculty of Humanities of the University of the Witwatersrand in partial fulfilment of the requirements for the degree of Master of Arts in History 04 May 2015 / This report analyzes the reasons behind the adoption of out growing schemes (sistemas canavieiros) by two Mozambican sugar companies, namely the Companhia do Buzi and the Açucareira de Moçambique as well as the impacts of the companies’ decision on the mills as well as on local communities. Analyzing the adoption of out growing schemes is relevant due to the fact that the Companhia do Buzi and the Açucareira de Moçambique were the only two out of ten Mozambican sugar companies to collaborate with out growers. All the out growers were Portuguese citizens or ‘civilized’ Africans. The report also analyses the reasons and the impacts of the collapse of those schemes in the early post-colonial period. The report argues that the mills adopted out growing schemes to face the long term shortage and increasing costs of African agricultural labour. This strategy solved their problems but left the out growers indebted and frustrated and local communities dispossessed. On the collapse of the out growing schemes, the report argues that it resulted from the increasing lack of economic feasibility of sugar cane growing, which was a result of economic crisis and the authorities’ hostility towards the out growers.

Thesis (MTech (Horticultural Science))--Cape Peninsula University of Technology, 2016. / Hydroponics, i.e. plant cultivation in mineral-rich water is a synergy between plant, human, and machine. For decades the hydroponic garden has been offered on horticultural markets, and was repeatedly innovated to better meet consumer horticultural needs. Currently, platform convergences with electronic control systems can possibly enable more efficient products for direct consumer hydroponic cultivation. This means that, like many appliances in the home; hydroponic plant cultivation can become somewhat automated. Marketing and product innovation can help calibrate optimal New Product Development NPD of hydroponic gardens for people. The literature review grasps how consumers are subjected to a changing environment together with changing technology such as hydroponics, plant nutrition, and even garden automation. Market research frameworks namely Morphological Analysis (MA) and Conjoint Analysis (CA) are the tools deployed here for profiling and prioritising these products for horticultural consumers. Firstly, a qualitative analysis identifies conceptual sets for structures, inputs, and controls, which all harmonise into new intersections cultivation, hydroponics, and automation and the e-garden concepts. The MA next produces, and organises secondary data into constraints for the CA. Here, general hydroponic cultivation is first decomposed into all its many component parts which collectively describe the whole, where these parts are then classed along various attributes namely: garden plane xA, automation xB, performance xC, organics xD, and price xE So garden plane is composed of level and vertical gardens, garden automation is composed of manual and automatic gardens, garden performance is composed of casual and high-performance gardens, garden organics is composed of non-organic and organic gardens, and garden price although quantitative is simply composed of R2500 and R5000. These classes of attributed data can now become treated as categorical factors using indicator or dummy variables. Secondly, the CA determines how these attributes are most preferred by horticultural consumers at garden centre clusters. This involves measuring respondent preferences levels, to compute the part-worth utility for each attribute found in the MA. Factors such as garden organics, price, and automation hold adjusted alpha significance. Mainly, garden organics contributed to response effects, while price has negative slope and is second, while automation comes third. A combination of garden automation and organics is found to optimise consumer utility for Hydroponic Garden(s) HG.This research illuminates how horticultural consumers may prefer various HG, by understanding HG and how they can better benefit these people.

Optimal nutritional management of growing pigs is constrained by lack of quantitative information on the response of animals between 30 and 110 kg live weight to dietary energy content. Under 'ideal' conditions modern genotypes appear to adjust feed intake to maintain a constant DE intake over a much wider range of dietary energy concentrations than previously thought (Mullan et al, 1998). However, under commercial pen conditions, voluntary feed intake is lower, pigs respond in terms of both growth rate and feed conversion to dietary DE density considerably above the levels currently thought to maximise biological and economic responses. The present study was designed to provide information on the response of growing pigs to dietary energy content under ideal and commercial housing conditions for two growth periods 30-60kg liveweight and 60-100kg liveweight. The results of the pigs kept under individual (ideal) housed conditions were consistent with the literature in that they adjusted their voluntary feed intake with digestible energy density to maintain a constant energy intake. The results of the pigs kept in groups (commercial) housing conditions tended to increase their daily energy intake as the energy density of the feed increased. This increase in energy intake improved the growth rate of the pigs and increased the fat deposition of those pigs. Economic analysis of the experiments involving pigs in groups indicates that formulating diets to a least cost per megajoule of digestible energy is not the most profitable point to set the digestible energy density. Modelling programs need to be used to determine where the least cost per unit of growth of the pig occurs. This is the most economical digestible energy density to formulate too. This will have major impact on the cost of production of piggery operations as the cost of energy is the single most important parameter in the cost of producing a pig.

The Cattle Value Discovery System (CVDS) was developed to predict growth and feed requirements of individual cattle fed in groups based on animal, diet, and environment information (Tedeschi et al., 2006). Evaluations of the CVDS using several databases of finishing cattle were conducted to determine the accuracy and precision of the model in predicted dry matter required (DMR) of pen-fed cattle. As well, the sensitivity of the model's predictions to deviations from actual ration metabolizable energy (ME) value was conducted. A meta-analysis of growing and finishing steers evaluated to model's accuracy in predicting DMR of individually fed steers, and the relationships between several model-predicted variables and actual performance and efficiency measures. Results for the first CVDS model evaluation involving pen-fed Santa Gertrudis cattle fed finishing diets revealed that accurate predictions of DMR are possible. The average mean bias for both steers and heifers was 2.43%. The sensitivity analysis of dietary ME values revealed that the model tends to consistently over- and under-predict DMR when the ME values are under- and over-estimated, respectively. However the ranking of pens was not affected by this mis-estimation of diet ME. In the second evaluations, both methods (mean body weight; MBW, dynamic iterative model; DIM) of CVDS were highly accurate and precise in allocating feed to pens of steers fed diverse types of diets and environmental conditions, with both models having a mean bias under 4%. The DIM model was slightly more accurate than the MBW model in predicting DMR. An evaluation of sources of variation revealed that for both models a large portion of the error was random, indicating that further work is needed to account for this variation. The meta-analysis study revealed that the model was able to account for 64% and 67% of the variation in observed dry matter intake (DMI) for growing and finishing steers, respectively. The two model-predicted efficiency measures, the ratio of DMR to average daily gain (ADG) and predicted intake difference (PID), were strongly to moderately correlated with their observed efficiency counterparts. In growing and finishing steers, DMR: ADG was able to account for 76% and 64% of the variation in observed feed conversion ratio (FCR) in growing and finishing studies, respectively. Strong correlations were also found between residual feed intake (RFI) and PID, suggesting that there may also be some similarity on these two measurements.

The Cattle Value Discovery System (CVDS) was developed to predict growth and feed requirements of individual cattle fed in groups based on animal, diet, and environment information (Tedeschi et al., 2006). Evaluations of the CVDS using several databases of finishing cattle were conducted to determine the accuracy and precision of the model in predicted dry matter required (DMR) of pen-fed cattle. As well, the sensitivity of the model’s predictions to deviations from actual ration metabolizable energy (ME) value was conducted. A meta-analysis of growing and finishing steers evaluated to model’s accuracy in predicting DMR of individually fed steers, and the relationships between several model-predicted variables and actual performance and efficiency measures. Results for the first CVDS model evaluation involving pen-fed Santa Gertrudis cattle fed finishing diets revealed that accurate predictions of DMR are possible. The average mean bias for both steers and heifers was 2.43%. The sensitivity analysis of dietary ME values revealed that the model tends to consistently over- and under-predict DMR when the ME values are under- and over-estimated, respectively. However the ranking of pens was not affected by this mis-estimation of diet ME. In the second evaluations, both methods (mean body weight; MBW, dynamic iterative model; DIM) of CVDS were highly accurate and precise in allocating feed to pens of steers fed diverse types of diets and environmental conditions, with both models having a mean bias under 4%. The DIM model was slightly more accurate than the MBW model in predicting DMR. An evaluation of sources of variation revealed that for both models a large portion of the error was random, indicating that further work is needed to account for this variation. The meta-analysis study revealed that the model was able to account for 64% and 67% of the variation in observed dry matter intake (DMI) for growing and finishing steers, respectively. The two model-predicted efficiency measures, the ratio of DMR to average daily gain (ADG) and predicted intake difference (PID), were strongly to moderately correlated with their observed efficiency counterparts. In growing and finishing steers, DMR: ADG was able to account for 76% and 64% of the variation in observed feed conversion ratio (FCR) in growing and finishing studies, respectively. Strong correlations were also found between residual feed intake (RFI) and PID, suggesting that there may also be some similarity on these two measurements.

Despite being a common childhood complaint there is little research on growing pains. Existing research is inconsistent with regard to sample selection and prevalence rates. There are only two English language intervention studies, and with the exception of associations noted in prevalence research, there has been no systematic research on the potential impact of growing pains on daily activities. Lack of a universal definition of growing pains poses difficulty for both diagnosis and research. The purposes of the current investigation were to propose a definition of growing pains grounded in literature and clinical practice, to develop a conceptual model of growing pains, and to understand childrens experiences with growing pains. A mixed-method research program involved four phases. In phase I, a survey of physicians indicated the following definition of growing pains: Intermittent pain of unknown etiology, occurring nocturnally in the lower limbs. Features that may occur in some cases, but not part of the definition, include arm pain and daytime pain. In phase II, non-parametric statistical analyses of child, familial, and environmental variables in a rheumatology clinic database were conducted to determine potential risk factors for growing pains. Logistic regression modeling indicated an association between growing pains and maternal illness or rash during the pregnancy, maternal smoking during the pregnancy, delayed pull to standing (i.e., greater than age 10 months), and family histories of back pain and arthritis. Potential mechanisms for these empirical associations are explored. In phase III, qualitative interviews with children were conducted to develop a grounded theory of how children process their experiences. Children engaged in a process of evaluating their current and past experiences of growing pains to determine how to manage specific pain episodes. Their evaluation was influenced by how they understood their pain which in turn was influenced by their intrapersonal and interpersonal experiences. Phase IV integrated results and existing literature to develop a conceptual model of growing pains which outlines characteristic features, predisposing factors, triggers, alleviating actions, and associated psychosocial features. Implications of the process theory and the conceptual model of growing pains with regard to clinical practice and future research are discussed.

Despite being a common childhood complaint there is little research on growing pains. Existing research is inconsistent with regard to sample selection and prevalence rates. There are only two English language intervention studies, and with the exception of associations noted in prevalence research, there has been no systematic research on the potential impact of growing pains on daily activities. Lack of a universal definition of growing pains poses difficulty for both diagnosis and research. The purposes of the current investigation were to propose a definition of growing pains grounded in literature and clinical practice, to develop a conceptual model of growing pains, and to understand childrens experiences with growing pains. A mixed-method research program involved four phases. In phase I, a survey of physicians indicated the following definition of growing pains: Intermittent pain of unknown etiology, occurring nocturnally in the lower limbs. Features that may occur in some cases, but not part of the definition, include arm pain and daytime pain. In phase II, non-parametric statistical analyses of child, familial, and environmental variables in a rheumatology clinic database were conducted to determine potential risk factors for growing pains. Logistic regression modeling indicated an association between growing pains and maternal illness or rash during the pregnancy, maternal smoking during the pregnancy, delayed pull to standing (i.e., greater than age 10 months), and family histories of back pain and arthritis. Potential mechanisms for these empirical associations are explored. In phase III, qualitative interviews with children were conducted to develop a grounded theory of how children process their experiences. Children engaged in a process of evaluating their current and past experiences of growing pains to determine how to manage specific pain episodes. Their evaluation was influenced by how they understood their pain which in turn was influenced by their intrapersonal and interpersonal experiences. Phase IV integrated results and existing literature to develop a conceptual model of growing pains which outlines characteristic features, predisposing factors, triggers, alleviating actions, and associated psychosocial features. Implications of the process theory and the conceptual model of growing pains with regard to clinical practice and future research are discussed.

The Cattle Value Discovery System (CVDS) was developed to predict growth and feed requirements of individual cattle fed in groups based on animal, diet, and environment information (Tedeschi et al., 2006). Evaluations of the CVDS using several databases of finishing cattle were conducted to determine the accuracy and precision of the model in predicted dry matter required (DMR) of pen-fed cattle. As well, the sensitivity of the model’s predictions to deviations from actual ration metabolizable energy (ME) value was conducted. A meta-analysis of growing and finishing steers evaluated to model’s accuracy in predicting DMR of individually fed steers, and the relationships between several model-predicted variables and actual performance and efficiency measures. Results for the first CVDS model evaluation involving pen-fed Santa Gertrudis cattle fed finishing diets revealed that accurate predictions of DMR are possible. The average mean bias for both steers and heifers was 2.43%. The sensitivity analysis of dietary ME values revealed that the model tends to consistently over- and under-predict DMR when the ME values are under- and over-estimated, respectively. However the ranking of pens was not affected by this mis-estimation of diet ME. In the second evaluations, both methods (mean body weight; MBW, dynamic iterative model; DIM) of CVDS were highly accurate and precise in allocating feed to pens of steers fed diverse types of diets and environmental conditions, with both models having a mean bias under 4%. The DIM model was slightly more accurate than the MBW model in predicting DMR. An evaluation of sources of variation revealed that for both models a large portion of the error was random, indicating that further work is needed to account for this variation. The meta-analysis study revealed that the model was able to account for 64% and 67% of the variation in observed dry matter intake (DMI) for growing and finishing steers, respectively. The two model-predicted efficiency measures, the ratio of DMR to average daily gain (ADG) and predicted intake difference (PID), were strongly to moderately correlated with their observed efficiency counterparts. In growing and finishing steers, DMR: ADG was able to account for 76% and 64% of the variation in observed feed conversion ratio (FCR) in growing and finishing studies, respectively. Strong correlations were also found between residual feed intake (RFI) and PID, suggesting that there may also be some similarity on these two measurements.

After entering WTO, Taiwan faces the challenges of globalization. At the same time, migration of manufacturing industries to mainland China seems to be an endless trend. To avoid failure, firms have to make constant changes, expand their sizes, and seek strategies for sustaining profit growth under the severe competitive environment of today¡¦s global markets. To maintain competitive advantages, small and medium enterprise have to leverage their resources and competences for sustainable profitability and growth by careful strategies formulation. The diversification processes to expand a firm¡¦s size and business fields are related to its competence and its efficiency of leveraging resources. This research is about the relationship between resources based view and diversifying strategies. Based on the diversification process of company L, we explore the strategies for the case company by considering changes in industry environment and the company¡¦s conditions ,with the evaluation of the company¡¦s competence and resources. The findings are: 1. The fields of new businesses for diversification of a company are restrained by their existing resources. 2.The diversification will be more likely to success, if the products to be carried in the new business are highly connected to the company¡¦s current customers. 3.The new business will eventually need new resources ,which will be accumulated and become one of the firm¡¦s important resources.

The Cattle Value Discovery System (CVDS) was developed to predict growth and feed requirements of individual cattle fed in groups based on animal, diet, and environment information (Tedeschi et al., 2006). Evaluations of the CVDS using several databases of finishing cattle were conducted to determine the accuracy and precision of the model in predicted dry matter required (DMR) of pen-fed cattle. As well, the sensitivity of the model's predictions to deviations from actual ration metabolizable energy (ME) value was conducted. A meta-analysis of growing and finishing steers evaluated to model's accuracy in predicting DMR of individually fed steers, and the relationships between several model-predicted variables and actual performance and efficiency measures. Results for the first CVDS model evaluation involving pen-fed Santa Gertrudis cattle fed finishing diets revealed that accurate predictions of DMR are possible. The average mean bias for both steers and heifers was 2.43%. The sensitivity analysis of dietary ME values revealed that the model tends to consistently over- and under-predict DMR when the ME values are under- and over-estimated, respectively. However the ranking of pens was not affected by this mis-estimation of diet ME. In the second evaluations, both methods (mean body weight; MBW, dynamic iterative model; DIM) of CVDS were highly accurate and precise in allocating feed to pens of steers fed diverse types of diets and environmental conditions, with both models having a mean bias under 4%. The DIM model was slightly more accurate than the MBW model in predicting DMR. An evaluation of sources of variation revealed that for both models a large portion of the error was random, indicating that further work is needed to account for this variation. The meta-analysis study revealed that the model was able to account for 64% and 67% of the variation in observed dry matter intake (DMI) for growing and finishing steers, respectively. The two model-predicted efficiency measures, the ratio of DMR to average daily gain (ADG) and predicted intake difference (PID), were strongly to moderately correlated with their observed efficiency counterparts. In growing and finishing steers, DMR: ADG was able to account for 76% and 64% of the variation in observed feed conversion ratio (FCR) in growing and finishing studies, respectively. Strong correlations were also found between residual feed intake (RFI) and PID, suggesting that there may also be some similarity on these two measurements.